# Currently just a mean of 3 values
M = matrix(runif(1000,min=-7,max=7), ncol=10)
ref_fM = stats::filter(M, c(1/3,1/3,1/3), circular=FALSE)
- fM = epclust:::.epclustFilter(M)
+ fM = epclust:::epclustFilter(M)
#Expect an agreement on all inner values
expect_equal(dim(fM), c(100,10))
- expect_equal(fM[2:99,], ref_fM[,2:99])
+ expect_equal(fM[2:99,], ref_fM[2:99,])
- #For border values, just apply a "by-hand" mean
- expect_equal(fM[1,], colMeans(rbind(M[1,],M[2,],M[100,])))
- expect_equal(fM[100,], colMeans(rbind(M[100,],M[99,],M[1,])))
-}
+ #Border values should be unchanged
+ expect_equal(fM[1,], M[1,])
+ expect_equal(fM[100,], M[100,])
+})